摘要
风储协调控制中需要处理多个具有不一致性的子目标,各子目标的权重系数对控制效果具有关键作用。首先,通过仿真分析验证了基于固定赋权法的多目标优化控制难以适应风电出力的随机性特点。然后,提出一种通过网格化搜索进行权重系数在线调优的动态赋权方法。为了判定最优的权重系数,提出了一种基于隶属度与熵权法的评价方法。算例分析表明,所述方法能够根据风电功率波动情况、储能荷电状态(SOC)及储能出力等情况,自适应地改变各子目标的权重系数,从而在平抑风电功率波动的同时,提高了储能充放电效率,并显著改善对储能SOC的控制效果。
The coordinated control of wind power and battery energy storage system(BESS)needs to deal with multiple inconsistent sub-objectives.The sub-objectives are weighted by weighting factors,which will greatly influence the control effects.Firstly,it is verified by simulations that,constant weighting factors-based multi-objective optimization control cannot adapt the random nature of wind power.Secondly,a dynamic weighting method is proposed,which is based on gridding searching of the optimal weighting factors.In order to determine the optimal weighting factors,an evaluation method by using the membership function and entropy weight method is proposed.It is shown by simulation studies that the proposed method has significant effects on the output power and state of charge(SOC)control of BESS while smoothing wind power,thus adaptively adjusting the weighting factor of each objective according to the wind power fluctuations,the SOC and the charge/discharge power of BESS.
出处
《电力系统自动化》
EI
CSCD
北大核心
2016年第12期94-99,206,共7页
Automation of Electric Power Systems
基金
国家科技支撑计划资助项目(2013BAA01B04)
国家电网公司科技项目(520940140021)~~
关键词
风力发电
储能系统
多目标优化
熵权法
动态赋权
模型预测控制
wind power generation
energy storage system
multi-objective optimization
entropy weight method
dynamic weighting
model predictive control